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NeMa: Fast Graph Search with Label Similarity

Summary: NeMa: neighborhood-based subgraph search for labeled, heterogeneous networks. It defines a unified node-level cost combining structure and label similarity to yield top-k matches; NP-hard, solved with a heuristic inference-model and optimizations, outperforming keyword search and baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10667
Venue
VLDB
Year
2013
Pagerank
8.5572574e-05
Overall Rank
2,551 | 82.26%
DOI
-

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